tensor_test.cc

/*
  Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
  You may obtain a copy of the License at
  http://www.apache.org/licenses/LICENSE-2.0
  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  See the License for the specific language governing permissions and
  limitations under the License.
*/

#include "paddle/framework/tensor.h"
#include <gtest/gtest.h>
#include <string>

TEST(Tensor, Dims) {
  using namespace paddle::framework;
  using namespace paddle::platform;
  Tensor tt;
  tt.Resize({2, 3, 4});
  DDim dims = tt.dims();
  ASSERT_EQ(arity(dims), 3);
  for (int i = 0; i < 3; ++i) {
    EXPECT_EQ(i + 2, dims[i]);
  }
}

TEST(Tensor, DataAssert) {
  paddle::framework::Tensor src_tensor;

  bool caught = false;
  try {
    src_tensor.data<double>();
  } catch (paddle::platform::EnforceNotMet err) {
    caught = true;
    std::string msg =
        "holder_ should not be null\nTensor holds no memory. Call "
        "Tensor::mutable_data first.";
    const char* what = err.what();
    for (size_t i = 0; i < msg.length(); ++i) {
      ASSERT_EQ(what[i], msg[i]);
    }
  }
  ASSERT_TRUE(caught);
}

/* following tests are not available at present
   because Memory::Alloc() and Memory::Free() have not been ready.
*/
TEST(Tensor, MutableData) {
  using namespace paddle::framework;
  using namespace paddle::platform;
  {
    Tensor src_tensor;
    float* p1 = nullptr;
    float* p2 = nullptr;
    // initialization
    p1 = src_tensor.mutable_data<float>(make_ddim({1, 2, 3}), CPUPlace());
    EXPECT_NE(p1, nullptr);
    // set src_tensor a new dim with large size
    // momery is supposed to be re-allocated
    p2 = src_tensor.mutable_data<float>(make_ddim({3, 4}), CPUPlace());
    EXPECT_NE(p2, nullptr);
    EXPECT_NE(p1, p2);
    // set src_tensor a new dim with same size
    // momery block is supposed to be unchanged
    p1 = src_tensor.mutable_data<float>(make_ddim({2, 2, 3}), CPUPlace());
    EXPECT_EQ(p1, p2);
    // set src_tensor a new dim with smaller size
    // momery block is supposed to be unchanged
    p2 = src_tensor.mutable_data<float>(make_ddim({2, 2}), CPUPlace());
    EXPECT_EQ(p1, p2);
  }

#ifdef PADDLE_WITH_CUDA
  {
    Tensor src_tensor;
    float* p1 = nullptr;
    float* p2 = nullptr;
    // initialization
    p1 = src_tensor.mutable_data<float>(make_ddim({1, 2, 3}), GPUPlace());
    EXPECT_NE(p1, nullptr);
    // set src_tensor a new dim with large size
    // momery is supposed to be re-allocated
    p2 = src_tensor.mutable_data<float>(make_ddim({3, 4}), GPUPlace());
    EXPECT_NE(p2, nullptr);
    EXPECT_NE(p1, p2);
    // set src_tensor a new dim with same size
    // momery block is supposed to be unchanged
    p1 = src_tensor.mutable_data<float>(make_ddim({2, 2, 3}), GPUPlace());
    EXPECT_EQ(p1, p2);
    // set src_tensor a new dim with smaller size
    // momery block is supposed to be unchanged
    p2 = src_tensor.mutable_data<float>(make_ddim({2, 2}), GPUPlace());
    EXPECT_EQ(p1, p2);
  }
#endif
}

TEST(Tensor, ShareDataWith) {
  using namespace paddle::framework;
  using namespace paddle::platform;
  {
    Tensor src_tensor;
    Tensor dst_tensor;
    // Try to share data form uninitialized tensor
    bool caught = false;
    try {
      dst_tensor.ShareDataWith<float>(src_tensor);
    } catch (paddle::platform::EnforceNotMet err) {
      caught = true;
      std::string msg =
          "holder_ should not be null\nTensor holds no memory. Call "
          "Tensor::mutable_data first.";
      const char* what = err.what();
      for (size_t i = 0; i < msg.length(); ++i) {
        ASSERT_EQ(what[i], msg[i]);
      }
    }
    ASSERT_TRUE(caught);

    src_tensor.mutable_data<int>(make_ddim({2, 3, 4}), CPUPlace());
    dst_tensor.ShareDataWith<int>(src_tensor);
    ASSERT_EQ(src_tensor.data<int>(), dst_tensor.data<int>());
  }

#ifdef PADDLE_WITH_CUDA
  {
    Tensor src_tensor;
    Tensor dst_tensor;
    src_tensor.mutable_data<int>(make_ddim({2, 3, 4}), GPUPlace());
    dst_tensor.ShareDataWith<int>(src_tensor);
    ASSERT_EQ(src_tensor.data<int>(), dst_tensor.data<int>());
  }
#endif
}

TEST(Tensor, Slice) {
  using namespace paddle::framework;
  using namespace paddle::platform;
  {
    Tensor src_tensor;
    src_tensor.mutable_data<int>(make_ddim({5, 3, 4}), CPUPlace());
    Tensor slice_tensor = src_tensor.Slice<int>(1, 3);
    DDim slice_dims = slice_tensor.dims();
    ASSERT_EQ(arity(slice_dims), 3);
    EXPECT_EQ(slice_dims[0], 2);
    EXPECT_EQ(slice_dims[1], 3);
    EXPECT_EQ(slice_dims[2], 4);

    uintptr_t src_data_address =
        reinterpret_cast<uintptr_t>(src_tensor.data<int>());
    uintptr_t src_mutable_data_address = reinterpret_cast<uintptr_t>(
        src_tensor.mutable_data<int>(src_tensor.dims(), CPUPlace()));
    uintptr_t slice_data_address =
        reinterpret_cast<uintptr_t>(slice_tensor.data<int>());
    uintptr_t slice_mutable_data_address = reinterpret_cast<uintptr_t>(
        slice_tensor.mutable_data<int>(slice_tensor.dims(), CPUPlace()));
    EXPECT_EQ(src_data_address, src_mutable_data_address);
    EXPECT_EQ(slice_data_address, slice_mutable_data_address);
    EXPECT_EQ(src_data_address + 3 * 4 * 1 * sizeof(int), slice_data_address);
  }

#ifdef PADDLE_WITH_CUDA
  {
    Tensor src_tensor;
    src_tensor.mutable_data<double>(make_ddim({6, 9}), GPUPlace());
    Tensor slice_tensor = src_tensor.Slice<double>(2, 6);
    DDim slice_dims = slice_tensor.dims();
    ASSERT_EQ(arity(slice_dims), 2);
    EXPECT_EQ(slice_dims[0], 4);
    EXPECT_EQ(slice_dims[1], 9);

    uintptr_t src_data_address =
        reinterpret_cast<uintptr_t>(src_tensor.data<double>());
    uintptr_t src_mutable_data_address = reinterpret_cast<uintptr_t>(
        src_tensor.mutable_data<double>(src_tensor.dims(), GPUPlace()));
    uintptr_t slice_data_address =
        reinterpret_cast<uintptr_t>(slice_tensor.data<double>());
    uintptr_t slice_mutable_data_address = reinterpret_cast<uintptr_t>(
        slice_tensor.mutable_data<double>(slice_tensor.dims(), GPUPlace()));
    EXPECT_EQ(src_data_address, src_mutable_data_address);
    EXPECT_EQ(slice_data_address, slice_mutable_data_address);
    EXPECT_EQ(src_data_address + 9 * 2 * sizeof(double), slice_data_address);
  }
#endif
}

TEST(Tensor, CopyFrom) {
  using namespace paddle::framework;
  using namespace paddle::platform;
  {
    Tensor src_tensor;
    Tensor dst_tensor;
    CPUDeviceContext cpu_ctx((CPUPlace()));

    int* src_ptr = src_tensor.mutable_data<int>(make_ddim({3, 3}), CPUPlace());

    int arr[9] = {1, 2, 3, 4, 5, 6, 7, 8, 9};
    memcpy(src_ptr, arr, 9 * sizeof(int));

    auto cpu_place = new paddle::platform::CPUPlace();
    dst_tensor.CopyFrom<int>(src_tensor, *cpu_place, cpu_ctx);

    const int* dst_ptr = dst_tensor.data<int>();
    ASSERT_NE(src_ptr, dst_ptr);
    for (size_t i = 0; i < 9; ++i) {
      EXPECT_EQ(src_ptr[i], dst_ptr[i]);
    }

    Tensor slice_tensor = src_tensor.Slice<int>(1, 2);
    dst_tensor.CopyFrom<int>(slice_tensor, *cpu_place, cpu_ctx);
    const int* slice_ptr = slice_tensor.data<int>();
    dst_ptr = dst_tensor.data<int>();
    ASSERT_NE(dst_ptr, slice_ptr);
    for (size_t i = 0; i < 3; ++i) {
      EXPECT_EQ(dst_ptr[i], slice_ptr[i]);
    }
  }
#ifdef PADDLE_WITH_CUDA
  {
    Tensor src_tensor;
    Tensor gpu_tensor;
    Tensor dst_tensor;

    int* src_ptr = src_tensor.mutable_data<int>(make_ddim({3, 3}), CPUPlace());

    int arr[9] = {1, 2, 3, 4, 5, 6, 7, 8, 9};
    memcpy(src_ptr, arr, 9 * sizeof(int));

    // CPU Tensor to GPU Tensor
    auto gpu_place = new paddle::platform::GPUPlace(0);
    CUDADeviceContext gpu_ctx(*gpu_place);
    gpu_tensor.CopyFrom<int>(src_tensor, *gpu_place, gpu_ctx);

    // GPU Tensor to CPU Tensor
    auto cpu_place = new paddle::platform::CPUPlace();
    dst_tensor.CopyFrom<int>(gpu_tensor, *cpu_place, gpu_ctx);

    // Sync before Compare Tensors
    gpu_ctx.Wait();
    const int* dst_ptr = dst_tensor.data<int>();
    ASSERT_NE(src_ptr, dst_ptr);
    for (size_t i = 0; i < 9; ++i) {
      EXPECT_EQ(src_ptr[i], dst_ptr[i]);
    }

    Tensor slice_tensor = src_tensor.Slice<int>(1, 2);

    // CPU Slice Tensor to GPU Tensor
    gpu_tensor.CopyFrom<int>(slice_tensor, *gpu_place, gpu_ctx);

    // GPU Tensor to CPU Tensor
    dst_tensor.CopyFrom<int>(gpu_tensor, *cpu_place, gpu_ctx);

    // Sync before Compare Slice Tensors
    gpu_ctx.Wait();
    const int* slice_ptr = slice_tensor.data<int>();
    dst_ptr = dst_tensor.data<int>();
    ASSERT_NE(dst_ptr, slice_ptr);
    for (size_t i = 0; i < 3; ++i) {
      EXPECT_EQ(dst_ptr[i], slice_ptr[i]);
    }
  }
#endif
}

TEST(Tensor, CopyFromVector) {
  using namespace paddle::framework;
  using namespace paddle::platform;
  {
    std::vector<int> src_vec = {1, 2, 3, 4, 5, 6, 7, 8, 9};
    Tensor cpu_tensor;

    // Copy to CPU Tensor
    cpu_tensor.Resize(make_ddim({3, 3}));
    auto cpu_place = new paddle::platform::CPUPlace();
    CPUDeviceContext cpu_ctx(*cpu_place);
    cpu_tensor.CopyFromVector<int>(src_vec, cpu_ctx);

    // Compare Tensors
    const int* cpu_ptr = cpu_tensor.data<int>();
    const int* src_ptr = src_vec.data();
    ASSERT_NE(src_ptr, cpu_ptr);
    for (size_t i = 0; i < 9; ++i) {
      EXPECT_EQ(src_ptr[i], cpu_ptr[i]);
    }

    src_vec.erase(src_vec.begin(), src_vec.begin() + 5);
    cpu_tensor.Resize(make_ddim({2, 2}));
    cpu_tensor.CopyFromVector<int>(src_vec, cpu_ctx);
    cpu_ptr = cpu_tensor.data<int>();
    src_ptr = src_vec.data();
    ASSERT_NE(src_ptr, cpu_ptr);
    for (size_t i = 0; i < 5; ++i) {
      EXPECT_EQ(src_ptr[i], cpu_ptr[i]);
    }

    delete cpu_place;
  }

#ifdef PADDLE_WITH_CUDA
  {
    std::vector<int> src_vec = {1, 2, 3, 4, 5, 6, 7, 8, 9};
    Tensor cpu_tensor;
    Tensor gpu_tensor;
    Tensor dst_tensor;

    // Copy to CPU Tensor
    cpu_tensor.Resize(make_ddim({3, 3}));
    auto cpu_place = new paddle::platform::CPUPlace();
    CPUDeviceContext cpu_ctx(*cpu_place);
    cpu_tensor.CopyFromVector<int>(src_vec, cpu_ctx);

    // Copy to GPUTensor
    gpu_tensor.Resize(make_ddim({3, 3}));
    auto gpu_place = new paddle::platform::GPUPlace();
    CUDADeviceContext gpu_ctx(*gpu_place);
    gpu_tensor.CopyFromVector<int>(src_vec, gpu_ctx);
    // Copy from GPU to CPU tensor for comparison
    dst_tensor.CopyFrom<int>(gpu_tensor, *cpu_place, gpu_ctx);

    // Sync before Compare Tensors
    gpu_ctx.Wait();
    const int* src_ptr = src_vec.data();
    const int* cpu_ptr = cpu_tensor.data<int>();
    const int* dst_ptr = dst_tensor.data<int>();
    ASSERT_NE(src_ptr, cpu_ptr);
    ASSERT_NE(src_ptr, dst_ptr);
    for (size_t i = 0; i < 9; ++i) {
      EXPECT_EQ(src_ptr[i], cpu_ptr[i]);
      EXPECT_EQ(src_ptr[i], dst_ptr[i]);
    }

    src_vec.erase(src_vec.begin(), src_vec.begin() + 5);

    cpu_tensor.Resize(make_ddim({2, 2}));
    cpu_tensor.CopyFromVector<int>(src_vec, cpu_ctx);
    gpu_tensor.Resize(make_ddim({2, 2}));
    gpu_tensor.CopyFromVector<int>(src_vec, gpu_ctx);
    dst_tensor.CopyFrom<int>(gpu_tensor, *cpu_place, gpu_ctx);

    // Sync before Compare Tensors
    gpu_ctx.Wait();
    src_ptr = src_vec.data();
    cpu_ptr = cpu_tensor.data<int>();
    dst_ptr = dst_tensor.data<int>();
    ASSERT_NE(src_ptr, cpu_ptr);
    ASSERT_NE(src_ptr, dst_ptr);
    for (size_t i = 0; i < 5; ++i) {
      EXPECT_EQ(src_ptr[i], cpu_ptr[i]);
      EXPECT_EQ(src_ptr[i], dst_ptr[i]);
    }

    delete cpu_place;
    delete gpu_place;
  }
#endif
}

TEST(Tensor, ReshapeToMatrix) {
  using namespace paddle::framework;
  using namespace paddle::platform;
  Tensor src;
  int* src_ptr = src.mutable_data<int>({2, 3, 4, 9}, CPUPlace());
  for (int i = 0; i < 2 * 3 * 4 * 9; ++i) {
    src_ptr[i] = i;
  }
  Tensor res = ReshapeToMatrix<int>(src, 2);
  ASSERT_EQ(res.dims()[0], 2 * 3);
  ASSERT_EQ(res.dims()[1], 4 * 9);
}